ABSTRACT Heart disease is the leading cause of death in the United States. Coronary heart disease (CHD) is the most common type of heart disease. Every year, millions of Americans suffer otherwise preventable cardiac events resulting in 500,000 deaths and $200 billion dollars of economic damage each year. The prevalence of CHD varies by ethnicity. Nevertheless, fortunately, CHD related morbidity and mortality can be prevented through the early identification of those at risk to undergo lifestyle modifications and medical treatment. However, the current risk screening approaches are not sensitive across all ethnic groups, are expensive and require the aggregation of multiple tests. Usually, even after these tests have been conducted, additional procedures such as an ECG, stress test and coronary angiogram are required for CHD status ascertainment. These steps are costly and more importantly, hinder timely decision-making by physicians. Therefore, a more sensitive tool that is capable of ascertaining risk for CHD prior to an acute event, especially one that captures ethnicity specific risk could lead to more effective prevention and treatment for all members of our society. Using resources from the Framingham Heart Study (FHS), we have developed an integrated genetic- epigenetic assessment tool that incorporates the effects of genetic variation on DNA methylation (GxMeth effects) that may overcome many of these shortcomings and be that NextGen Precision Medicine screening tool for CHD. In this Phase I application, we seek to test the generalizability and translation of our tool for CHD incidence prediction in an independently collected cohort of African American subjects characterized for CHD. We will take advantage of high performance computational techniques to understand whether our approach works in a non-FHS population. Subsequently, to demonstrate translational feasibility of predictive markers, we will couple our simple blood draw based approach and the droplet digital PCR (ddPCR) technology to develop and validate methylation sensitive ddPCR (MSddPCR) assays. This approach uses DNA from as little as a single drop of blood, does not require extensive collection of clinical variables and will find widespread use as a quantitative biomarker for CHD in clinical, civil and pharmaceutical drug development related applications. Ultimately, the approaches proposed in this application will result in the introduction of a Precision Medicine tool encompassing an algorithm and a panel of MSddPCR assays based on a strong scientific premise for the prediction of CHD incidence. It will also serve as a proof-of-concept project that will lead to a full-scale Phase II examination to prospectively predict the onset of CHD in a large multi-ethnic cohort as implemented in a set of easy-to-conduct MSddPCR assays that take advantage of the Bio-Rad ddPCR platform that is in the process of gaining regulatory approval.